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Learning of distant state predictions by the orbitofrontal cortex in humans

Author

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  • G. Elliott Wimmer

    (Max Planck University College London Centre for Computational Psychiatry and Ageing Research
    University College London)

  • Christian Büchel

    (University Medical Center Hamburg-Eppendorf)

Abstract

Representations of our future environment are essential for planning and decision making. Previous research in humans has demonstrated that the hippocampus is a critical region for forming and retrieving associations, while the medial orbitofrontal cortex (OFC) is an important region for representing information about recent states. However, it is not clear how the brain acquires predictive representations during goal-directed learning. Here, we show using fMRI that while participants learned to find rewards in multiple different Y-maze environments, hippocampal activity was highest during initial exposure and then decayed across the remaining repetitions of each maze, consistent with a role in rapid encoding. Importantly, multivariate patterns in the OFC-VPFC came to represent predictive information about upcoming states approximately 30 s in the future. Our findings provide a mechanism by which the brain can build models of the world that span long-timescales to make predictions.

Suggested Citation

  • G. Elliott Wimmer & Christian Büchel, 2019. "Learning of distant state predictions by the orbitofrontal cortex in humans," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10597-z
    DOI: 10.1038/s41467-019-10597-z
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    Cited by:

    1. Ondrej Zika & Katja Wiech & Andrea Reinecke & Michael Browning & Nicolas W. Schuck, 2023. "Trait anxiety is associated with hidden state inference during aversive reversal learning," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    2. Nir Moneta & Mona M. Garvert & Hauke R. Heekeren & Nicolas W. Schuck, 2023. "Task state representations in vmPFC mediate relevant and irrelevant value signals and their behavioral influence," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    3. Evan M. Russek & Rani Moran & Yunzhe Liu & Raymond J. Dolan & Quentin J. M. Huys, 2024. "Heuristics in risky decision-making relate to preferential representation of information," Nature Communications, Nature, vol. 15(1), pages 1-16, December.

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